Abteilung Umweltsozialwissenschaften

River rehabilitation aims at alleviating negative effects of human impacts such as loss of biodiversity and reduction of ecosystem services. Such interventions entail difficult trade-offs between different ecological and often socio-economic objectives. Multi-Criteria Decision Analysis (MCDA) is a very suitable approach that helps assessing the current ecological state and prioritizing river rehabilitation measures in a standardized way, based on stakeholder or expert preferences. Applications of MCDA in river rehabilitation projects are often simplified, i.e. using a limited number of objectives and indicators, assuming linear value functions, aggregating individual indicator assessments additively, and/or assuming risk neutrality of experts. Here, we demonstrate an implementation of MCDA expert preference assessments to river rehabilitation and provide ample material for other applications. To test whether the above simplifications reflect common expert opinion, we carried out very detailed interviews with five river ecologists and a hydraulic engineer. We defined essential objectives and measurable quality indicators (attributes), elicited the experts´ preferences for objectives on a standardized scale (value functions) and their risk attitude, and identified suitable aggregation methods. The experts recommended an extensive objectives hierarchy including between 54 and 93 essential objectives and between 37 to 61 essential attributes. For 81% of these, they defined non-linear value functions and in 76% recommended multiplicative aggregation. The experts were risk averse or risk prone (but never risk neutral), depending on the current ecological state of the river, and the experts´ personal importance of objectives. We conclude that the four commonly applied simplifications clearly do not reflect the opinion of river rehabilitation experts. The optimal level of model complexity, however, remains highly case-study specific depending on data and resource availability, the context, and the complexity of the decision problem.

Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization.

River monitoring and assessment programs are important tools to quantify the condition of river ecosystems, identify deficits, and provide preliminary indication of how to improve them. But, they are limited in delivering comparable assessment results across national or transnational borders, aggregating site-specific assessments into broader scale assessments, and supporting river management decisions. We present a multi-criteria decision analysis approach for improving the comparability of ecological assessment methods of different origin and for combining these assessments into a joint procedure. The approach consists of seven consecutive steps. The most central ones concern the hierarchical allocation of ecological assessment endpoints, and the harmonization of the scoring procedure of attributes (ecological indicators or assets) to a common scale from 0 to 1. We demonstrate the approach integrating three programs developed to assess the hydromorphological river condition in Switzerland, Germany, and the USA. In our example, the integrated assessment produces comparable results for the whole range from natural to impacted rivers, while data continuity with original assessments was maintained. Our approach provides a common assessment standard due to the definition of the minimum amount of information required, is flexible regarding measurement and assessment endpoints, and bridges the gap between river quality assessment and management.

Increasing pressure on mountain water resources is making it necessary to address water governance issues in a transdisciplinary way. This entails drawing on different disciplinary perspectives, different types of knowledge, and different interests to answer complex governance questions. This study identifies strategies for addressing specific challenges to transdisciplinary knowledge production aiming at sustainable and reflective water governance. The study draws on the experiences of 5 large transdisciplinary water governance research projects conducted in Austria and Switzerland (Alp-Water-Scarce, MontanAqua, Drought-CH, Sustainable Water Infrastructure Planning, and an integrative river management project in the Kamp Valley). Experiences were discussed and systematically analyzed in a workshop and subsequent interviews. These discussions identified 4 important challenges to interactions between scientists and stakeholders—ensuring stakeholder legitimacy, encouraging participation, managing expectations, and preventing misuse of data and research results—and explored strategies used by the projects to meet them. Strategies ranged from key points to be considered in stakeholder selection to measures that enhance trustful relationships and create commitment.